stock_zh_a_disclosure_relation_cninfo

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations declare readOnlyHint=true and destructiveHint=false, which already establish safe read behavior. The description adds the data source URL and return type, but does not disclose rate limits, pagination, data freshness, or any caveats about the returned disclosure data. It does not contradict annotations; it simply provides minimal extra behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and follows a consistent docstring structure. The title, URL, and parameters are listed with little waste, though the duplicated '开始时间' for end_date is a clear error that should be fixed. It is not front-loaded with a single-sentence summary, but it remains relatively efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the burden of explaining return values, but it only states that the result is a DataFrame for the given symbol. It does not explain what the scheduled disclosure ('预约披露') data contains, what columns are returned, or how the date range interacts with the survey. An agent cannot tell if this is the correct tool for a specific disclosure relationship query without additional context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides no parameter descriptions, so the docstring's param blocks are the only source of meaning. It defines symbol as stock code, market with an explicit choice set, and dates as start/end time. However, end_date is incorrectly described as '开始时间' (start time) instead of '结束时间', and the date format is only inferable from defaults. This partial but flawed documentation earns a mid score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a source title and URL but never states the tool's action. The return type is specified as pandas.DataFrame for the given symbol, but the data content is only implied by the title '预约披露调研'. No explicit verb like 'query' or 'list', and no differentiation from sibling tools such as stock_zh_a_disclosure_report_cninfo.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. There is no mention of use cases, prerequisites, or exclusion conditions. The only contextual hint is the URL, which does not help an agent choose among the many cninfo-related functions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.